Why businesses need to invest in data-driven strategies to innovate

Data strategies within organisations are fast becoming a key competitive differentiator and necessity for innovation, as they affect a multitude of business decisions from risk analysis, customer experience, and storage. A recent PwC survey found that 83% of companies expect data and analytics will become increasingly important in the decision-making process over the next five years.

Leading organisations are more likely to differentiate themselves from their competitors based on their data platform. The ability for a platform to converge disparate forms of data, consume, and manage that data to make intelligent business decisions will be the next frontier to creating a better, more secure customer journey.

Using big data to relieve business pressures

There’s a growing trend amongst Australian businesses to gain insight from operational and analytic data. This stems from a pressure to innovate whilst cutting costs at the same time. Big data and analytics should be leveraged by businesses to inspire organisation-wide innovation. Technologies such as automated decision systems give managers real-time alerts on cost-cutting opportunities, without requiring the managers to perform extensive research.

Although having access to massive amounts of data is often seen as the major benefit of utilising big data, the real-time nature of the data is also vitally important. Real-time analytics mean businesses are able to estimate various metrics such as consumer confidence, which previously was only measureable retrospectively.

Nowadays, we are seeing real-time analytics across industries from banking and financial services to retail. For example, retail giant Amazon’s recommendation engine leverages real-time analytics to provide product recommendations to shoppers, and it has been reported that Amazon generates approximately 35% of their revenue through recommendations. These types of analytics are becoming more frequently used adding considerable power to prediction.

The battle between platforms

Now that data analytics is commonplace within business, the point of difference comes from the data platform itself, which is increasingly becoming the point of differentiation for leading organisations.

Predictive analytics is just one example of a data platform with competitive advantage, as it allows big data and business intelligence come together.

Credit: Merkushev | Dreamstime.com

As a result, the platforms powering predictive analytics are becoming increasingly important as they allow businesses to have access to capabilities such as data mining, and applying machine learning and artificial intelligence algorithms to optimise business processes and uncover new statistical patterns. For example, smart buildings and their security systems are leveraging machine learning to aid in facial recognition. These systems are able to recognise measurable characteristics such as the distance between facial features, the shape of the head as well as moles, scars and birthmarks to determine the identity of individual picked up by security systems.

In addition to predictive analytics platforms, selecting converged data platforms is another way to gain competitive advantage, due to its ability to connect siloes. Data siloes such as data warehouse, message middleware, search service, and document databases are notoriously difficult to connect, and organisations must look holistically at how these connect and influence each other. Convergence of these data silos leads to real-time data to action, single data copy, easy convergence, and a horizontal scale – all processes that improve and speed up the data analytics processes that power leading organisations.

Digital transformation and big data

Digital transformation is often used as a buzzword, but when given the definition it deserves, can be responsible for companies embracing a culture of change as well as ensuring ongoing competitiveness. Big data and digital transformation gives businesses the ability to make meaningful, strategic adjustments that minimise costs and maximise results at a base level.

If organisations know what consumers and employees are doing currently, they are able to create projections for what they will do in the future. Furthermore, businesses can start implementing changes to address their needs and goals to keep them ahead of their competitors. The digital transformation process is not complete until a business adopts big data as a key component of their digital transformation strategy.

Data is helping businesses create new growth opportunities as they gain the ability to aggregate and analyse industry data. In this way, data about products and services, buyers and suppliers, consumer preferences and intent can be captured and analysed, inspiring organisational-wide digital change. In the increasingly digitised construction industry, we have seen big data leveraged through construction technology so projects are run efficiently and within budget – ensuring that construction companies maintain a competitive advantage.

It is up to forward-thinking leaders across sectors to begin to aggressively to build their organisations’ big data capabilities to ensure that competitive advantage is not lost.

Big data is rapidly becoming a crucial way for leading companies to outperform their competitors, as both established players and new entrants invest in data-driven strategies to innovate and compete.

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